The present invention relates to a method for controlling/regulating a process in a motor vehicle, in particular a combustion process, gear-shifting process, or braking process, with the help of a characteristics grid map. The characteristics map is defined by several performance quantities of the process, which is to be controlled or regulated, and is represented by data points that have corresponding characteristics-map values. The control/regulation of the process occurs in consecutive control cycles. In one control cycle, at least one characteristics-map value is determined from the characteristics map for an operating point of the process. In addition, adjacent data points, which define an interpolation range in which the operating point lies, are initially determined, and then interpolation is performed between the data points. The present invention also relates to a control/regulating device for implementing this method.
A central problem in realizing control systems or regulating systems, in particular in automotive engineering, is simulating characteristics of the subsystems, which are to be controlled or regulated, in a computing device of the control/regulating device. For example, from these internal simulations, important internal state variables, which cannot be directly measured online or are not measured for cost reasons, can be determined for a controller, or the values determined by the simulation are used for the direct control or regulation of a process.
For representing a model in a control/regulating device, there are two fundamentally different conventional approaches:
simulating the relevant physical-technical system characteristics using a mathematical model (for example a differential equation system); and
directly storing pertinent system data as a function of the relevant performance quantities (characteristics map).
For use in a motor vehicle, a characteristics map has the advantage of a low computing time requirement, since complicated model calculations are not necessary. Instead, the values corresponding to a specific operating point of a process can be taken directly from the characteristics map. The characteristics map also has advantages in regards to simplifying the application. In a model representation that has analytical equations that describe physical contexts, the applications engineer generally must have extensive knowledge of the model structure to be able to perform a targeted optimization. Since the influence of the parameters, which are to be adapted, usually extends to additional areas of the xe2x80x9caddress spacexe2x80x9d and a more or less strong coupling of the influences exists, a lengthy, iterative search for the optimum parameter combination may be necessary in some instances. By contrast, every data point adjustment in a characteristics-map representation has a clearly defined, strictly limited local effect. Therefore, detailed model knowledge or an iterative procedure are not necessary. A systematic, standardizable adjustment is possible and can even be automated in some instances.
For these reasons, using characteristics maps for controlling or regulating processes in mass-produced control/regulating devices is already widespread today. In motor vehicles, characteristics maps are used, for instance, for injection and ignition, and for precisely managing additional modern engine management system tasks. Characteristics maps are also widely used for providing complex model information in safety systems such as anti-lock braking systems (ABS), anti-spin regulation (ASR), and other systems, which ensure driving stability and/or safety, and/or influence braking action, as well as in numerous other applications such as automated transmissions.
The characteristics maps used can be one-dimensional (characteristic curves) or two or more-dimensional. Since the demands for functionality and precision in the processes, which are to be controlled or regulated, are constantly rising, it will be increasingly necessary in the future to link more than two performance quantities in a characteristics map. Moreover, an exact coordination of performance quantities, which influence one another, such as injection quantity, ignition-advance angle, acceleration enrichment, etc. will be necessary.
The characteristics map of the present method for controlling/regulating a process in a motor vehicle is designed as a characteristics grid map. The data points, which represent a characteristics grid map, are usually arrayed equidistant to each other. However, there are conventional characteristics grid maps, in which the data points are placed in the ranges of the input variables, in which ranges the function to be stored changes dramatically. To this end, the input variable is non-linearly mapped on the characteristics map using a data-point table having non-equidistant data-point distribution. Equidistant data-point distribution can then be expected again within the characteristics map.
German Patent No. 34 38 781 describes a method using a characteristics grid map to help control/regulate a process in a motor vehicle. However, the method described therein is limited to a two-dimensional characteristics grid map, i.e. to a characteristics grid map that is defined by two performance quantities of the process. German Patent No. 34 38 781 describes a square interpolation (bilinear interpolation) in FIG. 3 and the corresponding figure description, and a triangular interpolation in FIG. 4 and the corresponding figure description.
Within the framework of a square interpolation, four adjacent data points are first determined that define an interpolation square in which an operating point of the process to be controlled or regulated lies. Subsequently, bilinear interpolation is performed between the data points. In triangular interpolation, three adjacent data points are first determined that define an interpolation triangle in which the operating point of the process lies. Subsequently, interpolation is performed between the data points within the bounds of non-linear interpolation. The described square interpolation has the disadvantages that a relatively large program size must be made available and that producing the characteristics-map value corresponding to the operating point necessitates a relatively long running time. In contrast, the described triangular interpolation has the advantage of a smaller program size with respect to the square interpolation, and the disadvantage of a longer running time. Yet above all, program size (a cost factor) and the processing speed of a processing unit play a major role in the application of a conventional method for controlling/regulating a process in a motor vehicle. Furthermore, the described triangular interpolation is limited to use in a characteristics grid map that has equidistant data-point distribution at a distance of the power of two.
An object of the present invention is to provide a method and device for controlling/regulating a process in a motor vehicle that are universally employable for characteristics maps of any dimension and data-point distribution, that have a reduced computational time for interpolation for constant or not significantly worsening interpolation quality, and that have an interpolated characteristics-map surface that has a steady pattern without discontinuities.
The object of the present invention is achieved by a method and device for controlling/regulating a process in a motor vehicle that determines the characteristics-map value for the operating point within the framework of a linear interpolation from a minimum number of data points. The number of data points resulting from the number of performance quantities of the process, which define the characteristics map, plus one.
The linear interpolation can be performed using, for example, an interpolation approach involving barycentric coordinates. Barycentric coordinates are coordinates related to the interpolation range that determine corresponding weighting values for the characteristics-map values corresponding to the data points as a function of the position of the operating point between the data points.
Linear interpolation has the advantage that for every additional dimension of the characteristics map, i.e. for every additional performance quantity of the process, by which the characteristics map is defined, only one additional data point is necessary. By contrast, in the bilinear interpolation used in conventional methods, the number of data points for each additional dimension of the characteristics map increases exponentially.
Thus, in the method according to the present invention, the computational time for interpolation is significantly reduced by linearly interpolating a minimum number of data points, which result from the dimension of the characteristics map plus one, without diminishing the interpolation quality. Moreover, the interpolated characteristics-map surface has a steady pattern and no discontinuities. Finally, the method according to the present invention is universally applicable independent of the characteristics-map dimension.
According to an advantageous embodiment of the present invention, it is proposed that the characteristics grid map be defined by two performance quantities of the process, and in the control cycle for the operating point of the process. At least one characteristics-map value is determined from the characteristics map by first determining three adjacent data points, which define an interpolation triangle in which the operating point lies, and by then interpolating between the data points using the interpolation equation:
YW=(B1*Y1+B2*Y2+B3*Y3)/(B1+B2+B3),
wherein B1, B2, B3 are the areas of triangular sections, which are defined by the operating point and each of two data points, within the interpolation triangle, which is defined by specific data points.
Advantageously, the three adjacent data points, which define the interpolation triangle in which the operating point lies, are determined by first establishing the grid square of the characteristics map in which the operating point lies by searching a data-point table. Then, the interpolation triangle in which the operating point lies is determined within the established grid square by comparing the performance-quantity components of the operating point.
According to another advantageous embodiment of the present invention, the characteristics grid map be defined by three performance quantities of the process. The at least one characteristics-map value is determined from the characteristics map in the control cycle for the operating point of the process by initially determining four adjacent data points, which define an interpolation tetrahedron in which the operating point lies and by then interpolating between the data points using the interpolation equation:
YW=(B1*Y1+B2*Y2+B3*Y3+B4*Y4)/(B1+B2+B3+B4),
wherein B1, B2, B3, B4 are the volumes of tetrahedral sections, which are defined by the operating point and three data points, and are within the interpolation tetrahedron, which is defined by specific data points.
The characteristics grid map for the method according to the present invention may have any dimension. The method according to the present invention is not limited to using two or three-dimensional characteristics grid maps according to the aforementioned advantageous embodiments. For every additional dimension of the characteristics map, the interpolation equation must be expanded in the numerator by the addend Bn*Yn and in the denominator by the addend Bn.
To further reduce the computational time for interpolation, according to an exemplary embodiment of the present invention, the distances between two adjacent data points of the characteristics grid map be normalized to the value 1 prior to interpolating. In the case of a two-dimensional characteristics grid map, the result is an area of the interpolation triangle in which the operating point lies, i.e. for the sum of the areas of the triangular sections, an area of xc2xd=0.5. When both numerator and denominator of the interpolation equation are multiplied by 2, the result is the value 1 in the denominator. From this, the following interpolation equation results:
YW=2*(B1*Y1+B2*Y2+B3*Y3).
Thus, after normalizing, an additional multiplication function must be performed for interpolation. However, one division function and two addition functions are no longer necessary.
As a result of the characteristics-map access to the data-point tables, the data points for the interpolation calculation in a two-dimensional characteristics grid map are at (0,0), (1,1) and (1,0) or (0,1). As a result, equidistant data-point distribution can be expected within the characteristics map, thereby decidedly reducing the computational time for calculating the areas of the triangular sections. Thus, the areas of the triangular sections are calculated as follows:
2*B2=W1*S32xe2x88x92W2*S31=W1xe2x88x92W2, 
2*B3=xe2x88x92W1*S22+W2*S21=W2, 
2*B1=1xe2x88x922*(B2+B3)=1xe2x88x922*W1,
wherein W1, W2 are the coordinates of operating point W on the X1-axis or X2-axis. Furthermore, Si1 and Si2 are the coordinates of data points Si on the X1-axis or X2-axis of the coordinate system. The interpolation equation for a two-dimensional characteristics grid map is thereby simplified to:
YW=Y1+W1*(Y2xe2x88x92Y1)+W2*(Y3xe2x88x92Y2).
For characteristics-map dimensions n greater than 2, the interpolation equation is generally simplified to:       Y    W    =            Y      1        +          SUM      ⁢              {                                                            W                1                                            i                =                1                                      n                    *                      (                                          Y                                  (                                      l                    +                    1                                    )                                            -                              Y                1                                      )                          }            
The proposed simplification leads to a significant reduction in the computational time for the calculation of the areas of the triangular sections, and thus, to a simplification of the interpolation equation.
According to another advantageous embodiment of the present invention, the operating point and the calculated characteristics-map value are stored at the end of a control cycle and a check test is made at the start of the subsequent control cycle to determine if the operating point of the subsequent control cycle has remained the same. In this exemplary embodiment, the fact that the operating point typically travels through the characteristics map continuously and with a limited rate of change is taken into account. If the operating point of the subsequent control cycle is the same as the operating point of the previous control cycle, the stored characteristics-map value can be called up and used without having to interpolate. In this way, the average calculation time for interpolation can be significantly reduced. In a two-dimensional characteristics map, which is provided with such an accelerated access, only three values, namely the X1 and X2 coordinates of the old operating point and the corresponding interpolation result, must be stored for this purpose in a memory of the control/regulating device, for example in the RAM.
According to yet another exemplary embodiment of the present invention, intermediate values Y1 and Y(i+1)xe2x88x92Yi of the interpolation equation are stored at the end of a control cycle, and a check test is made at the beginning of the subsequent control cycle to determine if the operating point of the subsequent control cycle has remained within the same interpolation range. If this is the case, the stored intermediate values can be used for calculating the interpolation range. Thus, for example in a two-dimensional characteristics map, the computational time is reduced to two multiplication functions and two addition functions.